System for diagnosing and optimizing vectored DSL lines

ABSTRACT

In accordance with embodiments disclosed herein, there are provided methods, systems, mechanisms, techniques, and apparatuses for diagnosing and optimizing vectored DSL lines. For example, in one embodiment, such a system includes an interface to a first subset of a plurality of digital communication lines allocated to a vectored group and to a second subset of the plurality of digital communication lines which operate external to the vectored group; a Dynamic Spectral Management server (DSM server) to analyze the vectored group by performing the following operations for each of the plurality of digital communication lines in the vectored group: measuring a mitigated noise level for the digital communication line with crosstalk cancellation active, measuring a non-mitigated noise level for the digital communication line with crosstalk cancellation inactive, and comparing the mitigated noise level measured on the digital communication line with the non-mitigated noise level measured on the digital communication line. In such an embodiment, the DSM server of the system further issues optimization instructions based on the analysis. For example, by issuing optimization instructions for the vectored group, for lines external to the vectored group, or for both.

CLAIM OF PRIORITY

This application is a U.S. National Phase application under 35 U.S.C.§371 of International Application No. PCT/US2012/029677, filed Mar. 19,2012, entitled “SYSTEM FOR DIAGNOSING AND OPTIMIZING VECTORED DSLLINES”, the entire contents of which are incorporated herein byreference.

COPYRIGHT NOTICE

A portion of the disclosure of this patent document contains materialwhich is subject to copyright protection. The copyright owner has noobjection to the facsimile reproduction by anyone of the patent documentor the patent disclosure, as it appears in the Patent and TrademarkOffice patent file or records, but otherwise reserves all copyrightrights whatsoever.

TECHNICAL FIELD

The subject matter described herein relates generally to the field ofcomputing, and more particularly, to systems and methods for diagnosingand optimizing vectored DSL lines.

BACKGROUND

The subject matter discussed in the background section should not beassumed to be prior art merely as a result of its mention in thebackground section. Similarly, a problem mentioned in the backgroundsection or associated with the subject matter of the background sectionshould not be assumed to have been previously recognized in the priorart. The subject matter in the background section merely representsdifferent approaches, which in and of themselves may also correspond toembodiments of the claimed subject matter.

Vectored DSL technology aids in mitigating crosstalk effects thatdegrade performance in deployments of DSL lines operating at highspeeds. Crosstalk may be a significant noise source in multi-pair coppercables used for DSL transmission. High speed DSL deployments areparticularly vulnerable to crosstalk for both the downstream and theupstream transmission directions; data rates being limited typically byFar-End-Crosstalk (FEXT). When multiple DSL line pairs share the samecable they induce crosstalk into each other which negatively affectsperformance.

Vectored DSL uses advanced signal processing techniques to mitigatecrosstalk and thus, improve performance. However, where mitigationtechniques may be further improved, additional performance gains arepossible. Moreover, not all lines within a particular cable participatein a vectoring scheme, and thus, such lines are not subject to crosstalkmitigation techniques using conventional vectoring capabilities, yet,non-vectored lines may nevertheless negatively affect the operation ofvectored lines due to, for example, crosstalk coupling onto the vectoredlines.

The present state of the art may therefore benefit from systems andmethods for diagnosing and optimizing vectored DSL lines as describedherein.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments are illustrated by way of example, and not by way oflimitation, and will be more fully understood with reference to thefollowing detailed description when considered in connection with thefigures in which:

FIG. 1 illustrates an exemplary architecture in which embodiments mayoperate;

FIGS. 2A, 2B, 2C, and 2D illustrate alternative exemplary architecturesin which embodiments may operate;

FIGS. 3A, 3B, 3C, and 3D illustrate alternative exemplary architecturesin which embodiments may operate;

FIG. 4 illustrates exemplary binder re-configuration in accordance withwhich embodiments may operate;

FIG. 5 illustrates a diagrammatic representations of a system inaccordance with which embodiments may operate, be installed, integrated,or configured;

FIG. 6 is a flow diagram illustrating a method for diagnosing andoptimizing vectored DSL lines in accordance with described embodiments;and

FIG. 7 illustrates a diagrammatic representation of a machine in theexemplary form of a computer system, in accordance with one embodiment.

DETAILED DESCRIPTION

Described herein are systems and methods for diagnosing and optimizingvectored DSL lines.

For example, in one embodiment, such a system includes an interface to afirst subset of a plurality of digital communication lines allocated toa vectored group and interfaced to a second subset of the plurality ofdigital communication lines which operate external to the vectoredgroup. In such an embodiment, a Dynamic Spectral Management server (DSMserver) analyzes the vectored group by performing the followingoperations for each of the plurality of digital communication lines inthe vectored group: measuring a mitigated noise level for the digitalcommunication line with crosstalk cancellation active, measuring anon-mitigated noise level for the digital communication line withcrosstalk cancellation inactive, and comparing the mitigated noise levelmeasured on the digital communication line with the non-mitigated noiselevel measured on the digital communication line. In such an embodiment,the DSM server further issues optimization instructions. For example,the DSM server may issue instructions for the digital communicationlines in the vectored group, or issue instructions for the digitalcommunication lines external to the vectored group, or issueinstructions for both, based on the analysis of the vectored group.

Different vectoring implementations may cancel crosstalk with differentlevels of suppression, and the systems and mechanisms disclosed hereinare able to track how well vectoring is working. For example, such asystem may calculate what the current vectoring performance should beand compare this to actual reported signal to noise ratio (SNR), margin,and bit rate. If actual performance is below calculated performance,then the root cause of the performance degradation may be determined byexamining data reported by vectored lines such as reported channelresponses (Hlog), signal to noise ratio (SNR), quiet line noise PSDs(QLN), and pair-to-pair crosstalk couplings (Xlog). Reported data fromvectored lines may indicate anomalies and potential root causes, such asdetermining if crosstalk cancellation is limiting or inhibitingperformance or whether there are problems with excess crosstalk fromlines outside the vectored group into the vectored group. Individualvectored or non-vectored lines generating excessive crosstalk andaffected frequency bands may also be identified.

To isolate root causes, it helps to separate crosstalk from backgroundnoise, and to further separate the cancelled and un-cancelled componentsof the crosstalk. To estimate the residual Far-End Crosstalk (FEXT), anddetermine the effectiveness of vectoring for a given DSL line,quantities are presented on a linear scale rather than dB, as follows:

SNR(f) is: signal to noise ratio at frequency f as defined in G.993.2.

H(f) is: complex channel characteristic function at frequency f asdefined in G.993.2.

QLN(f) is: quiet line noise PSD (Power Spectral Density) at frequency fas defined in G.993.2.

S_(j)(f) is defined as: transmit PSD on line j. S_(j)(f) may beestimated from MREFPSD and fine gains, g, as defined in G.993.2.

Xlin_(ij)(f) is: the upstream or downstream FEXT coupling coefficientfrom pair j into pair i, as defined in G.993.5, where pair i is the pairbeing analyzed, in which the “pair” is a twisted pair line which isequivalent to a DSL line, a DSL loop, or a digital communication line asis described herein.

XT_(i) (f) is defined as: sum of the crosstalk from other vectored linesinto vectored DSL line i. This is the crosstalk that would have coupledinto the line if there were no vectoring applied, for example, whenmitigation techniques are inactive or switched off. XT_(i) (f) isunknown but may be estimated as the sum of S_(j)(f) times|Xlin_(ij)(f)|² from all surrounding vectored lines, except for thegiven line as follows:

${{XT}(f)} = {\sum\limits_{j \neq i}{{{Sj}(f)}{{XLOG}_{ij}(f)}}}$

By definition XT_(i)(f) is equal to the sum of RXT_(i)(f) andCXT_(i)(f), where RXT_(i)(f) is defined as the residual crosstalk, fromthe vectored lines, that remains after vectoring and where CXT_(i)(f) isdefined as the crosstalk that was removed by vectoring cancellation orprecoding. Both RXT_(i)(f) and CXT_(i)(f) are unknown. For simplicity,the index of the vectored line, i, will be omitted from now on.

N(f) is defined as: background noise plus crosstalk from lines that arenot in the same vectored group and lines in the vectored group that arenot cancelled. N(f) is unknown.

ALN(f) is defined as: active line noise PSD of a line. ALN(f) includesnoise input to the receiver plus noise due to receiver imperfectionswhile the line is active including front-end noise and quantization.ALN(f) is unknown.

A(f) is defined as: the noise PSD component due only to receiverimperfections while the line is active including front-end noise andquantization. A(f) is unknown.

When vectoring is not enabled: ALN_(NC)(f)=N(f)+A(f)+XT(f) (in which NCdenotes ALN and is calculated while crosstalk is not canceled).

When vectoring is enabled: ALN_(C)(f)=N(f)+A(f)+RXT(f) (in which Cdenotes ALN and is calculated while crosstalk is canceled).

QLN(f) is estimated for a given line during start-up or during loopdiagnostics mode. Vectoring is not implemented into this line whileQLN(f) is estimated.

QLN(f) may thus be written as: QLN(f)=N(f)+XT(f).

N(f) is then estimated since N(f)=QLN(f)−XT(f).

Estimation of the unknown spectra, ALN_(NC)(f), ALN_(C)(f), RXT(f), andCXT(f) is performed by reading SNR(f) when vectoring is enabled anddisabled into a given line.

First, disable vectoring into the given line. Then, SNR(f) is measured,with SNR(f)=Si(f)|H(f)|²/ALN_(NC)(f).

ALN_(NC)(f) is then estimated since ALN_(NC)(f) is equal toSi(f)|H(f)|²/SNR(f).

Second, re-enable vectoring into the given line.

SNR(f) is then measured when vector crosstalk cancellation isimplemented, with SNR(f)=S_(i)(f)|H(f)|²/ALN_(C)(f).

RXT(f) and CXT(f) are then estimated sinceCXT(f)=XT(f)−RXT(f)=ALN_(NC)(f)−ALN_(C)(f) and RXT(f)=XT(f)−CXT(f).

As an alternative, RXT(f) may be estimated with the following twooperations: QLN′(f) may also be estimated in the upstream directionwhile vectoring is enabled. And thus, QLN′(f)=N(f)+RXT(f), and thenRXT(f) may be estimated since RXT(f)=QLN′(f)−N(f), in the upstreamdirection only.

Next, ALN_(C)(f)=N(f)+A(f)+RXT(f), where A(f) is defined as the noisecomponent due to receiver imperfections while the line is activeincluding front-end noise and quantization.

A(f) may thus be estimated since A(f)=ALN_(C)(f)−N(f)−RXT(f).

Thus, the following noise components have all been estimated: receivernoise A(f), the residual uncancelled crosstalk from the lines in thevectored group, RXT(f), the cancelled crosstalk from the lines in thevectored group, CXT(f), and the background noise plus crosstalk fromlines that are not in the same vector group, N(f). These quantities maybe used to identify the effectiveness of vectoring, and verify properoperation of the vectoring receiver.

A relatively high A(f) indicates a poor receiver front end. A relativelyhigh ratio of RXT(f)/CXT(f) indicates poor vectoring performance. Arelatively high ratio of N(f)/XT(f) indicates that vectoring cannot orwill not have much effect and that perhaps the line should not bevectored. For example, where vectoring will not have much effect, thevectoring resources may be more beneficial if applied elsewhere.Furthermore, N(f) can be analyzed to identify the FEXT component fromthe lines in the non-vectored group. For example, this can be done byexploiting the Radio Frequency Interference (RFI) notching mechanism inDSL. If RFI notching is enabled, DSL transmit PSD should be reduced inpredefined frequency bands dedicated to, for example, amateur radiobroadcasts (e.g., ham radio) to avoid excessive interference to suchfrequency bands. As a result, N(f) will have negligible crosstalkcomponent in the predefined frequency bands, which are spread over allthe DSL frequency bands. The FEXT component can be identified bycomparing N(f) in these bands with other bands. This FEXT component canlater be employed for applying proper transmit PSD on the non-vectoredlines and provide the required protection to guarantee the performanceof the vectored lines.

Noise at the customer end of the line is often very different from thenoise at the network end of the line. Thus, the analyses presented heremay be applied separately at the upstream and downstream receivers. Moresophisticated estimators could be used in the same framework, such asusing maximum entropy to estimate the spectra.

In the following description, numerous specific details are set forthsuch as examples of specific systems, languages, components, etc., inorder to provide a thorough understanding of the various embodiments. Itwill be apparent, however, to one skilled in the art that these specificdetails need not be employed to practice the disclosed embodiments. Inother instances, well known materials or methods have not been describedin detail in order to avoid unnecessarily obscuring the disclosedembodiments.

In addition to various hardware components depicted in the figures anddescribed herein, embodiments further include various operations whichare described below. The operations described in accordance with suchembodiments may be performed by hardware components or may be embodiedin machine-executable instructions, which may be used to cause ageneral-purpose or special-purpose processor programmed with theinstructions to perform the operations. Alternatively, the operationsmay be performed by a combination of hardware and software, includingsoftware instructions that perform the operations described herein viamemory and one or more processors of a computing platform.

Embodiments also relate to a system or apparatus for performing theoperations herein. The disclosed system or apparatus may be speciallyconstructed for the required purposes, or it may comprise a generalpurpose computer selectively activated or reconfigured by a computerprogram stored in the computer. Such a computer program may be stored ina non-transitory computer readable storage medium, such as, but notlimited to, any type of disk including floppy disks, optical disks,flash, NAND, solid state drives (SSDs), CD-ROMs, and magnetic-opticaldisks, read-only memories (ROMs), random access memories (RAMs), EPROMs,EEPROMs, magnetic or optical cards, or any type of media suitable forstoring non-transitory electronic instructions, each coupled to acomputer system bus. In one embodiment, a non-transitory computerreadable storage medium having instructions stored thereon, causes oneor more processors within a Management Device, a traffic aggregationunit, and/or a traffic de-aggregator to perform the methods andoperations which are described herein. In another embodiment, theinstructions to perform such methods and operations are stored upon anon-transitory computer readable medium for later execution.

The algorithms and displays presented herein are not inherently relatedto any particular computer or other apparatus nor are embodimentsdescribed with reference to any particular programming language. It willbe appreciated that a variety of programming languages may be used toimplement the teachings of the embodiments as described herein.

FIG. 1 illustrates an exemplary architecture 100 in which embodimentsmay operate in compliance with the G.997.1 standard (also known asG.ploam). Asymmetric Digital Subscriber Line (ADSL) systems (one form ofDigital Subscriber Line (DSL) systems), which may or may not includesplitters, operate in compliance with the various applicable standardssuch as ADSL1 (G.992.1), ADSL-Lite (G.992.2), ADSL2 (G.992.3),ADSL2-Lite G.992.4, ADSL2+ (G.992.5) and the G.993.x emergingVery-high-speed Digital Subscriber Line or Very-high-bitrate DigitalSubscriber Line (VDSL) standards, as well as the G.991.1 and G.991.2Single-Pair High-speed Digital Subscriber Line (SHDSL) standards, allwith and without bonding.

The G.997.1 standard specifies the physical layer management for ADSLtransmission systems based on the clear, Embedded Operation Channel(EOC) defined in G.997.1 and use of indicator bits and EOC messagesdefined in the G.992.x, G.993.x and G.998.4 standards. Moreover, G.997.1specifies network management elements content for configuration, faultand performance management. In performing the disclosed functions,systems may utilize a variety of operational data (which includesperformance data) that is available at an Access Node (AN).

In FIG. 1, users terminal equipment 102 (e.g., a Customer PremisesEquipment (CPE) device or a remote terminal device, network node, LANdevice, etc.) is coupled to a home network 104, which in turn is coupledto a Network Termination (NT) Unit 108. Multiple xTU devices (“allTransceiver Unit” devices) are further depicted. An xTU providesmodulation for a DSL loop or line (e.g., DSL, ADSL, VDSL, etc.). In oneembodiment, NT unit 108 includes an xTU-R (xTU Remote), 122 (forexample, a transceiver defined by one of the ADSL or VDSL standards) orany other suitable network termination modem, transceiver or othercommunication unit. NT unit 108 also includes a Management Entity (ME)124. Management Entity 124 may be any suitable hardware device, such asa microprocessor, microcontroller, or circuit state machine in firmwareor hardware, capable of performing as required by any applicablestandards and/or other criteria. Management Entity 124 collects andstores, among other things, operational data in its ManagementInformation Base (MIB), which is a database of information maintained byeach ME capable of being accessed via network management protocols suchas Simple Network Management Protocol (SNMP), an administration protocolused to gather information from a network device to provide to anadministrator console/program; via Transaction Language 1 (TL1)commands, TL1 being a long-established command language used to programresponses and commands between telecommunication network elements; orvia a TR-69 based protocol. “TR-69” or “Technical Report 069” is inreference to a DSL Forum technical specification entitled CPE WANManagement Protocol (CWMP) which defines an application layer protocolfor remote management of end-user devices. XML or “eXtended MarkupLanguage” compliant programming and interface tools may also be used.

Each xTU-R 122 in a system may be coupled with an xTU-C (xTU Central) ina Central Office (CO) or other central location. The xTU-C 142 islocated at an Access Node (AN) 114 in Central Office 146. A ManagementEntity 144 likewise maintains an MIB of operational data pertaining toxTU-C 142. The Access Node 114 may be coupled to a broadband network 106or other network, as will be appreciated by those skilled in the art.Each of xTU-R 122 and xTU-C 142 are coupled together by a loop 112,which in the case of ADSL may be a twisted pair line, such as atelephone line, which may carry other communication services besides DSLbased communications. Either Management Entity 124 or Management Entity144 may implement and incorporate a Dynamic Spectrum Management (DSM)server 170 as described herein. The DSM server 170 may be operated by aservice provider or may be operated by a third party, separate from theentity which provides DSL services to end-users. Thus, in accordancewith one embodiment, the DSM server 170 is operated and managed by anentity which is separate and distinct from a telecommunications operatorresponsible for a plurality of digital communication lines. ManagementEntity 124 or Management Entity 144 may further store collected WANinformation and collected LAN information within an associated MIB.

Several of the interfaces shown in FIG. 1 are used for determining andcollecting operational data. The Q interface 126 provides the interfacebetween the Network Management System (NMS) 116 of the operator and ME144 in Access Node 114. Parameters specified in the G.997.1 standardapply at the Q interface 126. The near-end parameters supported inManagement Entity 144 may be derived from xTU-C 142, while far-endparameters from xTU-R 122 may be derived by either of two interfacesover the U-interface. Indicator bits and EOC messages may be sent usingembedded channel 132 and provided at the Physical Medium Dependent (PMD)layer, and may be used to generate the required xTU-R 122 parameters inME 144. Alternately, the Operations, Administration and Maintenance(OAM) channel and a suitable protocol may be used to retrieve theparameters from xTU-R 122 when requested by Management Entity 144.Similarly, the far-end parameters from xTU-C 142 may be derived byeither of two interfaces over the U-interface. Indicator bits and EOCmessage provided at the PMD layer may be used to generate the requiredxTU-C 142 parameters in Management Entity 124 of NT unit 108.Alternately, the OAM channel and a suitable protocol may be used toretrieve the parameters from xTU-C 142 when requested by ManagementEntity 124.

At the U-interface (also referred to as loop 112), there are twomanagement interfaces, one at xTU-C 142 (the U-C interface 157) and oneat xTU-R 122 (the U-R interface 158). The U-C interface 157 providesxTU-C near-end parameters for xTU-R 122 to retrieve over theU-interface/loop 112. Similarly, the U-R interface 158 provides xTU-Rnear-end parameters for xTU-C 142 to retrieve over the U-interface/loop112. The parameters that apply may be dependent upon the transceiverstandard being used (for example, G.992.1 or G.992.2). The G.997.1standard specifies an optional Operation, Administration, andMaintenance (OAM) communication channel across the U-interface. If thischannel is implemented, xTU-C and xTU-R pairs may use it fortransporting physical layer OAM messages. Thus, the xTU transceivers 122and 142 of such a system share various operational data maintained intheir respective MIBs.

Depicted within FIG. 1 is Dynamic Spectral Management server (DSMserver) 170 operating at various optional locations in accordance withseveral alternative embodiments. For example, DSM server 170 may belocated within central office 146 and interfaced broadband network 106(e.g., a WAN) via Network Management System (NMS) 116. In yet anotherembodiment, DSM server 170 is connected with a NT unit 108 or with xTU-R122 over the G-interface 159.

As used herein, the terms “user,” “subscriber,” and/or “customer” referto a person, business and/or organization to which communicationservices and/or equipment are and/or may potentially be provided by anyof a variety of service provider(s). Further, the term “customerpremises” refers to the location to which communication services arebeing provided by a service provider. For an example Public SwitchedTelephone Network (PSTN) used to provide DSL services, customer premisesare located at, near and/or are associated with the network termination(NT) side of the telephone lines. Example customer premises include aresidence or an office building.

As used herein, the term “service provider” refers to any of a varietyof entities that provide, sell, provision, troubleshoot and/or maintaincommunication services and/or communication equipment. Example serviceproviders include a telephone operating company, a cable operatingcompany, a wireless operating company, an internet service provider, orany service that may independently or in conjunction with a broadbandcommunications service provider offer services that diagnose or improvebroadband communications services (DSL, DSL services, cable, etc.).

Additionally, as used herein, the term “DSL” refers to any of a varietyand/or variant of DSL technology such as, for example, Asymmetric DSL(ADSL), High-speed DSL (HDSL), Symmetric DSL (SDSL), and/or Veryhigh-speed/Very high-bit-rate DSL (VDSL). Such DSL technologies arecommonly implemented in accordance with an applicable standard such as,for example, the International Telecommunications Union (I.T.U.)standard G.992.1 (a.k.a. G.dmt) for ADSL modems, the I.T.U. standardG.992.3 (a.k.a. G.dmt.bis, or G.adsl2) for ADSL2 modems, I.T.U. standardG.992.5 (a.k.a. G.adsl2plus) for ADSL2+ modems, I.T.U. standard G.993.1(a.k.a. G.vdsl) for VDSL modems, I.T.U. standard G.993.2 for VDSL2modems, I.T.U. standard G.993.5 for DSL modems supporting Vectoring,I.T.U. standard G.998.4 for DSL modems supporting retransmissionfunctionality, I.T.U. standard G.994.1 (G.hs) for modems implementinghandshake, and/or the I.T.U. G.997.1 (a.k.a. G.ploam) standard formanagement of DSL modems.

References to connecting a DSL modem and/or a DSL communication serviceto a customer are made with respect to exemplary Digital Subscriber Line(DSL) equipment, DSL services, DSL systems and/or the use of ordinarytwisted-pair copper telephone lines for distribution of DSL services, itshould be understood that the disclosed methods and apparatus tocharacterize and/or test a transmission medium for communication systemsdisclosed herein may be applied to many other types and/or variety ofcommunication equipment, services, technologies and/or systems. Forexample, other types of systems include wireless distribution systems,wired or cable distribution systems, coaxial cable distribution systems,Ultra High Frequency (UHF)/Very High Frequency (VHF) radio frequencysystems, satellite or other extra-terrestrial systems, cellulardistribution systems, broadband power-line systems and/or fiber opticnetworks. Additionally, combinations of these devices, systems and/ornetworks may also be used. For example, a combination of twisted-pairand coaxial cable interfaced via a balun connector, or any otherphysical-channel-continuing combination such as an analog fiber tocopper connection with linear optical-to-electrical connection at anOptical Network Unit (ONU) may be used.

The phrases “coupled to,” “coupled with,” connected to,” “connectedwith” and the like are used herein to describe a connection between twoelements and/or components and are intended to mean coupled/connectedeither directly together, or indirectly, for example via one or moreintervening elements or via a wired/wireless connection. References to a“communication system” are intended, where applicable, to includereference to any other type of data transmission system.

FIG. 2A illustrates an alternative exemplary architecture 200 in whichembodiments may operate. FIG. 2A depicts an interface 213 to a firstsubset of a plurality of digital communication lines 210 allocated to avectored group 211 and to a second subset of the plurality of digitalcommunication lines 210 which operate external 212 to the vectored group211. A Dynamic Spectral Management server (DSM server) 170 is furtherdepicted. In such an embodiment the DSM server is to analyze thevectored group 211 by performing the following operations for each ofthe plurality of digital communication lines 210 in the vectored group211: (a) measure a mitigated noise level 215 for the digitalcommunication line with crosstalk cancellation active (e.g., measuringthe parameter for each line within the plurality of digitalcommunication lines 210 allocated to the vectored group 211); (b)measure a non-mitigated noise level 216 for the digital communicationline with crosstalk cancellation inactive, and (c) compare the mitigatednoise level 215 measured on the digital communication line with thenon-mitigated noise level 216 measured on the digital communicationline. For example, for each line the mitigated noise level 215 and thenon-mitigated noise level 216 is compared. In such an embodiment, theDSM server 170 is further to issue optimization instructions 218 for thevectored group 211 based on the analysis of the vectored group 211. Inalternative embodiments, the DSM server 170 issues optimizationinstructions 218 for the non-vectored group or one or more linesexternal to the vectored group (e.g., one or more of the digitalcommunication lines 210 external to the vectored group 212 in the secondsubset of lines) based on the analysis of the vectored group 211. Inanother alternative embodiment, the DSM server 170 issues optimizationinstructions 218 for one or more of the lines in each of the vectoredgroup 211 and the non-vectored group based on the analysis of thevectored group 211. Thus, subsequent to the analysis of the vectoredgroup 211, any combination of lines, vectored or otherwise, may becaused to alter their operational behavior through subsequentinstruction from the DSM server 170.

The mitigated noise level 215 may be represented as ALN_(C)(f), forexample, when vectoring is enabled. The non-mitigated noise level 216may be represented as ALN_(NC)(f), for example, when vectoring is notenabled.

In one embodiment, the plurality of digital communication lines 210 areimplemented as a plurality of Digital Subscriber Lines (DSL lines). Inone embodiment, the first subset 211 of the plurality of digitalcommunication lines 210 allocated to the vectored group 211 are vectoredDSL lines.

FIG. 2B illustrates an alternative exemplary architecture 201 in whichembodiments may operate. In one embodiment, the DSM server 170 analyzesthe vectored group 211 by calculating an estimated noise level 220 andan estimated crosstalk level 221 for each of the plurality of digitalcommunication lines 210 in the vectored group 211. For example, N(f)representing the background noise plus crosstalk may be estimated andcompared with ALN_(C)(f) and ALN_(NC)(f) representing mitigated noiselevels and non-mitigated noise levels respectively.

In one embodiment, the DSM server 170 calculating the estimated noiselevel 220 for each of the plurality of digital communication lines 210in the vectored group 211 by calculating the total Far End Crosstalk(FEXT) Power Spectral Density (PSD) 222 received by each of theplurality of digital communication lines 210 in the vectored group 211.

In one embodiment, DSM server 170 calculates an estimated level ofcrosstalk interference 225 which was cancelled by vectoring within thevectored group 211. Such a calculation may help to assess how wellvectoring is working as applied to the vectored group 211 of digitalcommunication lines 210.

In one embodiment, the SNR(f) 217 and Quiet Line Noise Power SpectralDensity, QLN(f) 219, for each of the plurality of digital communicationlines 210 in the vectored group 211 are used by the DSM server 170 tocalculate a value for the mitigated noise level, a value for thenon-mitigated noise level 216, and a value for the baseline level ofinterference 224 on the respective digital communication line within thevectored group 211 when the interference (e.g., noise 223) attributableto the other digital communication lines 210 within the same vectoredgroup 211 is perfectly canceled.

FIG. 2C illustrates an alternative exemplary architecture 202 in whichembodiments may operate. PSD 230 is depicted on the vertical axis andFrequency (f) 231 is depicted on the horizontal axis of the graph.

In one embodiment, the mitigated noise level 215 represents a firstamount of noise measured on the respective digital communication linewithin the vectored group 211 while noise cancellation techniques areactive to cancel out crosstalk attributable to other digitalcommunication lines 210 within the same vectored group 211. In oneembodiment, the non-mitigated noise level 216 represents a second amountof noise measured on the respective digital communication line withinthe vectored group 211 while noise cancellation techniques are inactive.In one embodiment, the non-mitigated noise level 216 includesuncancelled interference from the other digital communication lines 210within the same vectored group 211. The difference between non-mitigatednoise level 216 and mitigated noise level 215 for a given line yieldsCXT_(i)(f) which is the crosstalk that was removed by vectoringcancellation when noise mitigation is active.

In one embodiment, the DSM server 170 measures a signal-to-noise ratio,SNR(f) 217, for each of the plurality of digital communication lines 210in the vectored group 211. In one embodiment, the estimated baselinelevel of interference 224 includes at least one of: an estimated levelof interference attributable to receiver electronics, the receiverelectronics being part of a receiver coupled with one of the pluralityof digital communication lines 210. For example, such a receiver mayoperate at or within a user's terminal equipment 102 as set forth atFIG. 1, within one of the Transceiver Units 142 and 122 shown at FIG. 1,or within other communication equipment connected with the digitalcommunication lines 210. In one embodiment, the estimated baseline levelof interference 224 includes an estimated level of interferenceattributable to an imperfect implementation of the crosstalkcancellation for the vectored group 211.

With reference again to FIG. 2B, in accordance with one embodiment, theDSM server 170 analyzes the vectored group 211 by: estimatingtheoretical Far end crosstalk (FEXT); comparing the estimatedtheoretical FEXT to the mitigated noise levels 215 measured for theplurality of digital communication lines 210 in the vectored group 211;determining effectiveness of the crosstalk cancellation for the vectoredgroup 211; and issuing commands to a Vectoring Control Entity (VCE)communicably interfaced with the vectored group 211. For example, byissuing commands in the form of optimization instructions 218.

In one embodiment, the DSM server 170 calculates an estimatedperformance gain based on the analysis of the vectored group 211 andcompares the estimated performance gain against a threshold. The DSMserver 170 may elect or decline to send optimization instructions 218based on whether or not an estimated performance gain exceeds a minimumthreshold. For example, where the gain is determined to be minimal,insufficient, or inconsequential, the DSM server may elect to applyvectoring resources elsewhere, or to apply a different set or type ofoptimization instructions in place of applying vectoring to a line.

FIG. 2D illustrates an alternative exemplary architecture 203 in whichembodiments may operate. PSD 230 is again depicted on the vertical axisand Frequency (f) 231 is depicted on the horizontal axis of the graph.

In one embodiment, the DSM server 170 identifies transmit Power SpectralDensity (PSD) and a type of an alien crosstalker based on a crosstalkcoupling frequency or a crosstalk coupling frequency range 232 affectingone or more of the plurality of digital communication lines 210 in thevectored group 211 based on the analysis of the vectored group 211. Asdepicted, a spike in PSD 230 is shown with regard to a particularcrosstalk coupling frequency range 232 indicating a probable aliencrosstalker.

With reference again to FIG. 2B, in accordance with one embodiment, theDSM server 170 performs noise-typing of an interference signal based onthe analysis of the vectored group 211 and identifies a source of theinterference signal based on the noise-typing. For example, noise-typingmay determine the type of noise which may be attributable tointerferences such as RFI (Radio Frequency Interference), crosstalk;impulse noise, noise in a certain frequency band or at certain powerlevels, and so forth. Based on the power level or measured PSD for theparticular frequency range, the crosstalk coupling frequency range 232may be typed against, or correlated with a known determinable source.

Impairment on vectored DSL lines, such as those in the vectored group211 may be determinable based on a determined crosstalk coupling (Xlog).Xlog may carry signatures of unwanted impairments such as watered-cable,bad-splice, wires with insufficient shielding, wires with insufficienttwisting, etc. Using field measurements for a network, it is possible toinvestigate the data and look for unique signatures.

In one embodiment, the DSM server 170 correlates the alien crosstalkerwith one of the plurality of lines in the second subset of digitalcommunication lines 210 which operate external 212 to the vectored group211 or with one of the plurality of digital communication lines 210 inthe vectored group 211 based on the crosstalk coupling frequency or thecrosstalk coupling frequency range 232 associated with the aliencrosstalker.

Profile optimization (PO) can be performed for multi-line vectoredsystems. Joint profile optimization of multiple DSL lines in a vectoredgroup 211 instead of performing profile optimization independentlyline-by-line is possible in cases where the vectored lines are notindependent. Such dependent cases include poor cancellation due totime-varying coupling from factors such as temperature variation oraerial cable movement. Profile optimization may include, for example,sending optimization instructions 218 from the DSM server to controltransmit power and spectra to reduce the effects of crosstalk from thosepoorly cancelled lines on the remaining pairs in a binder.

In one embodiment, the optimization instructions 218 include noisecancellation directed toward the identified alien crosstalker. In oneembodiment, the DSM server 170 calculates an estimated performance gainattributable to issuing the optimization instructions 218.

In one embodiment, the DSM server 170 identifies an alien crosstalkerbased on the analysis of the vectored group 211. In one embodiment, thealien crosstalker corresponds to one of: a non-vectored digitalcommunication line among the plurality of digital communication lines210; a non-vectored digital communication line within a common binderwith the plurality of digital communication lines 210 in the vectoredgroup 211; or a non-vector-friendly digital communication line among theplurality of digital communication lines 210 within the vectored group211.

In one embodiment, the non-vector-friendly digital communication line iscommunicably interfaced with a non-vector-friendly Digital SubscriberLine Modem (DSL modem) which does not support vectoring or does notimplement vectoring. For example, one of the users' terminal equipment102 devices as shown at FIG. 1 may be a legacy device or anon-compatible modem which cannot or does not implement vectoring.

In one embodiment, the DSM server 170 correlates the alien crosstalkerwith one of the plurality of lines in the second subset of digitalcommunication lines 210 which operate external 212 to the vectored group211 or with one of the plurality of digital communication lines 210 inthe vectored group 211 based on neighborhood information using DSM level2 joint spectral optimization among a selection of vectored lines,vector-friendly lines, and/or non-vector-friendly lines within the firstand second subsets of digital communication lines 210 which operatewithin and external 212 to the vectored group 211 respectively.

In one embodiment, a first alien crosstalker inside of the vectoredgroup 211 yields an estimated performance gain which is less than anestimated performance gain for a second alien crosstalker external 212to the vectored group 211. In such an embodiment, the first aliencrosstalker corresponds to one of the first subset 211 of digitalcommunication lines 210 allocated to the vectored group 211 and thesecond alien crosstalker corresponds to one of the second subset ofdigital communication lines 210 to operate external 212 to the vectoredgroup 211. Stated differently, the line which is already a member of thevectored group may benefit less, in terms of an estimated performancegain attributable to the proposed optimization instructions 218 incomparison to a line which is not already a member of the vectoredgroup.

In one embodiment, the DSM server 170 identifies an alien crosstalkeramong the plurality of digital communication lines 210 based on theanalysis of the vectored group 211 and the DSM server 170 issues theoptimization instructions 218 for the vectored group 211 based on thealien crosstalker being identified as one of the plurality of digitalcommunication lines 210 external 212 to the vectored group 211.

In one embodiment, the DSM server 170 identifies one or more digitalcommunication lines 210 external 212 to the vectored group 211 based onthe analysis of the vectored group 211 and performs at least one of thefollowing operations for the identified one or more digitalcommunication lines 210 external 212 to the vectored group 211: a) theDSM server 170 changes system parameters affecting at least one of thedigital communication lines 210 external 212 to the vectored group 211,and b) the DSM server 170 migrates at least one of the digitalcommunication lines 210 which operates external 212 to the vectoredgroup 211 to operate within the vectored group 211. For example, suchactions may be taken to institute remediation efforts based on thecrosstalkers being identified as having a high-potential for improvementto the overall operation of the vectored group 211. For example, wherean estimated performance gain exceeds a threshold, the DSM server 170may determine that taking an affirmative remedial action will beworthwhile in terms of performance gain and system optimization.

FIG. 3A illustrates an alternative exemplary architecture 300 in whichembodiments may operate. In particular, a cable 329 is shown havingbinders 330A, 330B, and 330C therein. Binder 330A has digitalcommunication lines connecting vectored group 305A with locations 320Avia DSLAM 315A. Binder 330B has digital communication lines connectingvectored group 305B with locations 320B via DSLAM 315B. Binder 330C hasdigital communication lines connecting a non-vectored group 310 of lineswith locations 320C via DSLAM 315C.

As noted above, the DSM server 170 may perform DSM level 2 jointspectral optimization among a selection of vectored lines usingneighborhood information. Such information is available with regard tothe various sets of locations 320A-C, each representing, for example, aneighborhood or a geographical area common to each particular set oflocations, such as 320A or 320B or 320C. In one embodiment theneighborhood information specifies at least cable and/or binderinformation associated with a given set of locations 320A-C.

A state machine for profile vectors may be utilized which includes aprofile for each vectored line. The state machine may be utilized toimprove stability and speeds of the entire vectored group, such asvectored group 305A and/or 305B. Such analysis and use of a statemachine for the profile vectors may be referred to as NeighborhoodProfile Optimization or NPO. A permanent record of vectoring performancedata and Xlog data may be captured and stored for future planningpurposes. Such a record may include information reflecting adetermination and performance tracking when a line leaves or joins avector group 305A-B. Neighborhood Profile Optimization may be utilizedto anticipate the impact of alien noise when vectoring is applied beforevectoring is actually applied on a line or group of lines, andNeighborhood Profile Optimization may be used to compare performancewhen a dominant crosstalker is on versus when it is off.

The arrangement of vectored groups 305A and 305B each allocated to arespective common binder 330A and 330B respectively and the non-vectoredgroup 310 not sharing a binder with the vectored groups 305A-Crepresents an optimal allocation scheme. However, it may not always bepossible to achieve such an allocation scheme. In other instances,re-arranging, re-routing, and re-allocating may improve the allocationscheme.

Managing vectored lines, such as those within vectored groups 305A and305B, managing vector friendly lines, and managing legacy lines, mayinclude identification of a non-vectored-friendly CPE connected to avectored DSLAM (Digital Subscriber Line Access Multiplexer) or an aliendisturber or alien crosstalker which is connected to a non-vectoredDSLAM (including an ADSL2/2+ line) limiting the performance of thevectored system. Non-vector friendly lines can disturb vectored linessynch, and other operating characteristics. Profile optimization for thenon-vectored-friendly CPE, or if possible the aliendisturber/crosstalker may minimize detrimental effects on the vectoredgroup, and may therefore yield an operational benefit, for example,initiated by issuing optimization instructions 218. Such optimizationinstructions may include, for example, DSM level II methods, powermanagement and rate control.

Vectoring diagnostics, and Xlog data may be used in conjunction with DSMlevel 2, joint DSM 2 spectral optimization, and DSM 3 vectoring, toachieve customer target bit-rates on vectored and non-vectored lines,for example, by optimizing vectored to non-vectored interference insituations where lines are mutually interfering so as to preventexcessive retraining or packet errors.

Information pertaining to neighborhood location and vector groups 305A-Bmay be used to enable optimal selection of vector groups 305A-B and toassign cancellation resources within a vector group. For example,assigning vector cancellation to lines that are indicated to be close toeach other based on neighborhood information, such as a known,estimated, or determined physical proximity of locations 320A-C within aparticular geographical location. This may be done based on DSLAMinformation or information from a serving terminal that can beconsidered as a part of overall neighborhood/cable information.

Vectored lines are synchronized allowing for accurate calculation ofnoise correlations. Neighborhood information can be combined with thiscorrelation information to estimate the location of the root source ofnoise, for example noise originating near some home(s) effecting linesin the same neighborhood.

Certain neighborhoods may benefit more than others from vectoring, andneighborhood information may be utilized to recommend upgrades fromnon-vectored to vectored systems during a roll-out prioritization phase,or in situations where not all components will be upgraded to vectoringcompatible devices.

Xlog data and vectoring performance analysis may be used to determinewhich lines and frequency bands should be vectored. This data may alsobe used to determine to which subscribers phantom circuits, and/orbonding should be deployed on to improve speeds or reaches.

Vectoring diagnostics may provide vital information to ensure fairnessamong several providers in specific regulatory environments. Forexample, in cases where bit-stream unbundling for VDSL is carried outwith one provider per line, the availability of Xlog data and vectoringperformance data may become essential for management of the cableinterests between different operators. In the bit-stream unbundlingcase, an entire infrastructure is managed by a single operator, and thenmonitoring for fairness becomes important as well as managing forfairness.

Vector resource allocation may be used to assist bandwidth allocation.For example, if the network serves an apartment complex and the complexpurchases the service, the bandwidth may be divided and reapportionedamong subscribers to some extent by assigning vectoring resources.

Phantom mode may be used in multi-line systems as well as thediagnostics unique to phantom mode. A measurement system that measurescommon mode voltages, powers, PSDs, FDR (Frequency-Domain Reflectometer)traces and TDR (Time-Domain Reflectometer) traces, etc. may be used todiagnose each individual wire used in phantom mode transmission,measurement system in contrast to conventional systems which measurequantities differentially across a wire pair. Similarly, a unique typeof single-ended line test (SELT) may be applied to phantom mode on asingle wire to ground instead of across a wire pair.

A “Cu-PON” (“Copper Passive Optical Network”) is a multidropping DSLarchitecture that enables DSL bandwidth sharing and increases data ratesthrough exploitation of all modes of crosstalk, particularly with theuse of vectored dynamic spectrum management. The Cu-PON shares bandwidthacross multiple copper pairs in a cable, enables variable numbers ofmultiple drop lines to each subscriber, and may use phantom mode andvectoring. The Cu-PON enables highly adaptable bandwidth allocation. TheCu-PON may be used to effectively feed multiple CPEs within the samelocation, such as a business or residence.

It is useful to know Xlog or Xlin for many purposes related to planning,resource allocation, profile optimization, and diagnostics. An estimatorexploits the fact that E[x_(p)x_(j)]˜=0 for p!=j. The resulting estimateis further improved by removing the bias inherent in the non-zero crosscorrelation of finite data sequences. When crosstalk is not beinghandled properly, DSL data including Xlog may be used for diagnosing thesituation and reassignment of vector-group, binder or both, asnecessary, to resolve the issue.

Thus, in accordance with some embodiments, the optimization instructions218 include re-allocating or reassigning lines into and out of avectored group.

FIG. 3B illustrates an alternative exemplary architecture 301 in whichembodiments may operate. In the example shown here, optimizationinstructions may yield an improvement by re-allocating all linesassociated with locations 320A to operate with vectored group 305A sothat all such lines traverse the same binder at 330A and participate inthe same vectoring scheme at 305A. In this example, the bold line fromlocations 320A may have been associated with another vectored groupother than 305A or may not have been assigned to a vectored group.

FIG. 3C illustrates an alternative exemplary architecture 302 in whichembodiments may operate. In the example shown here, optimizationinstructions may yield an improvement by changing the routing of a linefrom locations 320B such that it traverses binder 330B and participatesin the same vectored group 305B. Through neighborhood analysis, thelocations 320B may determined to share a common geographical location,such as a neighborhood, and thus, it may be beneficial to re-routecommunications for a particular location from, for example, a line 210in binder 330B and onto a line 210 in binder 330A.

In other embodiments, optimization instructions may yield an improvementby changing both the grouping and the routing of a line 210 servicing aparticular location 330A. For example, a location may be added tovectored group 305B and the line 210 servicing that location may bere-routed such that it shares a common binder with the other members ofvectored group 305B, such as binder 330B.

FIG. 3D illustrates an alternative exemplary architecture 303 in whichembodiments may operate. In the example shown here, optimizationinstructions may yield an improvement by changing the routing for theline due to the line's proximity with another line being analyzed. Forexample, choosing another line within binder 330C may be beneficialwhere border lines within binder 330C exhibit a strong coupling withborder lines of binder 330B, thus, selecting a different line within thesame binder 330C which is more distant from the border lines of 330B mayyield a benefit. Such grouping into lines, binders, and cables is commonwith twisted pair lines or loops used as digital communication lines210.

In accordance with one embodiment, issuing the optimization instructions218 for the vectored group 211 includes: changing one or more parametersaffecting operation of the vectored group 211, in which the one or moreparameters are selected from the group including: bit rate, margin,Power Spectral Density (PSD) limits, vectoring resource allocations, andImpulse Noise Protection (INP) settings.

In one embodiment, changing the one or more parameters affectingoperation of the vectored group 305A-B includes issuing the optimizationinstructions 218 to change the one or more parameters in at least oneof: a Digital Subscriber Line Access Multiplexer (DSLAM) 315A-Ccommunicably interfaced with at least one of the plurality of digitalcommunication lines in the vectored group 305A-B, one or more DSLAMs(e.g., one of 315B or 315C) adjacent to the first DSLAM (e.g., 315A),for example, the DSLAM adjacent to the first DSLAM may enable control ofthe transmit power or PSD of non-vectored lines which are identified ascreating crosstalk interference into the vectored group 305A-B.

Changing the one or more parameters may further include changing one ormore parameters in at least one of: a Customer Premises Equipment (CPE)modem communicably interfaced with at least one of the plurality ofdigital communication lines in the vectored group 305A-B or within a DSLElement Management System (EMS) communicably interfaced with at leastone of the plurality of digital communication lines in the vectoredgroup 305A-B.

In one embodiment, issuing the optimization instructions 218 for thevectored group 305A-B includes: a) dispatching orders to modify aconfiguration of one or more system elements communicably interfacedwith at least one of the plurality of communicably interfaced digitalcommunication lines; b) generating service recommendations includingservice upgrades, service downgrades, or different service options,based on the analysis of the vectored group 305A-B; c) initiating acustomer notification based on the analysis of the vectored group305A-B, the customer notification being directed to a customer ofservices associated with one of the plurality of communicably interfaceddigital communication lines; and d) initiating a service providernotification based on the analysis of the vectored group 305A-B, theservice provider notification being directed to a service provider ofservices associated at least one of the plurality of communicablyinterfaced digital communication lines. In one embodiment, issuing theoptimization instructions 218 includes initiating noise cancellationdirected toward an identified alien crosstalker.

In one embodiment, issuing the optimization instructions 218 for thevectored group 211 includes performing at least one of the followingoperations: a) changing system parameters affecting at least one of thedigital communication lines operating external (e.g., in thenon-vectored group 310) to the vectored group 305A-B, and b) migratingat least one of the digital communication lines operating external tothe vectored group to operating within the vectored group.

In accordance with one embodiment, a non-transitory computer readablestorage medium stores instructions that, when executed by a processor ina Dynamic Spectrum Management server (DSM server 170), the instructionscause the DSM server 170 to perform operations including: communicablyinterfacing with a plurality of digital communication lines 210;identifying, within the plurality of digital communication lines 210, avectored group 305A-B having a plurality of digital communication lines210 allocated thereto; analyzing the vectored group 305A-B by performingthe following sub-operations for each of the plurality of digitalcommunication lines 210 in the vectored group 305A-B: (a) measuring amitigated noise level for the digital communication line with crosstalkcancellation mitigation active, (b) measuring a non-mitigated noiselevel for the digital communication line with crosstalk cancellationmitigation inactive, and (c) comparing the mitigated noise levelmeasured on the digital communication line with the non-mitigated noiselevel measured on the digital communication line; and issuingoptimization instructions 218 for the vectored group 305A-B based on theanalysis of the vectored group 305A-B.

FIG. 4 illustrates exemplary binder re-configuration 400 in accordancewith which embodiments may operate. When vectored and non-vectored linesare mixed in the same binder and they cannot be separates into twoindependent binders, copper assignment within a binder might have anoperational benefit. Typically, operators have pair or line number andthe corresponding geometric location information.

As can be seen, lines within binder 450 are re-routed or reconfigured tomaximize distance between the various pairs or lines. This type ofrouting might be possible if the equipment vendor offers larger nodesizes for vectoring or some means of electronic cross connection of thevarious lines.

Within the binder 450, vectored lines may be placed together, asrepresented by the pairs associated with the number “1,” andnon-vectored lines associated with the number “2” are placed together,distant from the vectored lines. The same technique may additionally beapplied across to multiple binders within a cable, for the border pairswhich are in distinct binders but nevertheless in close proximity. In analternative embodiment, virtual binder groups may be created by groupinglines together with high crosstalk, but which are not necessarily in thesame physical cable binder, with similar operations performed on thevirtual binder.

FIG. 5 illustrates a diagrammatic representations of a system 500 inaccordance with which embodiments may operate, be installed, integrated,or configured.

In one embodiment, system 500 includes a memory 595 and a processor orprocessors 596. For example, memory 595 may store instructions to beexecuted and processor(s) 596 may execute such instructions.Processor(s) 596 may also implement or execute implementing logic 560having logic to implement the methodologies discussed herein. System 500includes communication bus(es) 515 to transfer transactions,instructions, requests, and data within system 500 among a plurality ofperipheral devices communicably interfaced with one or morecommunication buses 515. In one embodiment, system 500 includes acommunication bus 515 to interface, transfer, transact, relay, and/orcommunicate information, transactions, instructions, requests, and datawithin system 500, and among plurality of peripheral devices. System 500further includes management interface 525, for example, to receiverequests, return responses, and otherwise interface with networkelements located separately from system 500.

In some embodiments, management interface 525 communicates informationvia an out-of-band connection separate from DSL line basedcommunications, where “in-band” communications are communications thattraverse the same communication means as payload data (e.g., content)being exchanged between networked devices and where “out-of-band”communications are communications that traverse an isolatedcommunication means, separate from the mechanism for communicating thepayload data. An out-of-band connection may serve as a redundant orbackup interface over which to communicate control data between thesystem 500 and other networked devices or between the system 500 and athird party service provider.

System 500 further includes DSL line interface 530 to communicateinformation via a LAN based connection, to monitor connected DSL lines,DSL loops, DSL twisted pairs, and Digital communication lines which areinterfaced to system 500. System 500 further includes stored historicalinformation 550 that may be analyzed or referenced when conducting longterm trending analysis and reporting. System 500 may further includemultiple optimization instructions 555, any of which may be initiatedresponsive to analysis of the vectored and non-vectored lines. Forexample, corrective actions, additional diagnostics, information probes,configuration change requests, local commands, remote executioncommands, and the like may be specified by and triggered as optimizationinstructions 555. The stored historical information 550 and theoptimization instructions 555 may be stored upon a hard drive,persistent data store, a database, or other storage location withinsystem 500.

Distinct within system 500 is DSM server 501 which includes collectionmodule 570, analysis module 575, diagnostics module 580, andimplementation module 585. DSM server 501 may be installed andconfigured in a compatible system 500 as is depicted by FIG. 5, orprovided separately so as to operate in conjunction with appropriateimplementing logic 560 or other software.

In accordance with one embodiment, collection module 570 collectsinformation from available sources, such as from interfaced digitalcommunication lines over the DSL line interface 530 of system 500 orfrom other network elements via management interface 525. Analysismodule 575 analyzes the information retrieved via collection module 570.Analysis module 575 may further perform long term trending analysisbased on stored historical information 550 or conduct neighborhoodanalysis based on aggregation data yielded from multiple separate anddistinct digital communication lines. Diagnostics module 580 may conductspecialized diagnostic routines and algorithms in conjunction with orseparately from analysis module 575. Diagnostics module 580 may conductadditional probing diagnostics to retrieve or trigger the output ofadditional diagnostics information for further analysis. Implementationmodule 585 implements and initiates various optimization instructions555 including generating and instantiating instructions CPE modems,DSLAMs, and vectoring engines and hardware, and other network elements.

FIG. 6 is a flow diagram 600 illustrating a method for diagnosing andoptimizing vectored DSL lines in accordance with described embodiments.Method 600 may be performed by processing logic that may includehardware (e.g., circuitry, dedicated logic, programmable logic,microcode, etc.), software (e.g., instructions run on a processingdevice to perform various operations such as interfacing functions,collecting, monitoring, diagnosing and reporting information, andexecuting/initiating optimization instructions, calculations, or somecombination thereof). In one embodiment, method 600 is performed orcoordinated via DSM server such as that depicted at element 170 of FIG.1 and at element 501 of FIG. 5A. Some of the blocks and/or operationslisted below are optional in accordance with certain embodiments. Thenumbering of the blocks presented is for the sake of clarity and is notintended to prescribe an order of operations in which the various blocksmust occur. Additionally, operations from flow 600 may be utilized in avariety of combinations.

Method 600 begins with processing logic for communicably interfacingwith a plurality of digital communication lines at block 605.

At block 610, processing logic identifies a vectored group having aplurality of digital communication lines allocated thereto.

At block 615, processing logic analyzes the vectored group includingmeasuring and comparing a mitigated noise level and a non-mitigatednoise level. For example, processing logic measures a mitigated noiselevel for each digital communication line with crosstalk cancellationactive and processing logic measures a non-mitigated noise level foreach digital communication line with crosstalk cancellation inactive.The analysis further includes comparing the mitigated noise levelmeasured with the non mitigated noise level and conducting othernecessary calculations.

At block 620, processing logic issues optimization instructions for thevectored group based on the analysis of the vectored group (e.g.,changing parameters, dispatching orders, generating servicerecommendations, initiating a customer/service provider notification, ormigrating a line). For example, processing logic may change one or moreparameters affecting operation of the vectored group. Such processinglogic may dispatch orders to modify a configuration of one or moresystem elements communicably interfaced with at least one of theplurality of communicably interfaced digital communication lines.Processing logic may generate service recommendations including serviceupgrades, service downgrades, or different service options, based on theanalysis of the vectored group. Processing logic may initiate a customernotification based on the analysis of the vectored group. Processinglogic may initiate a service provider notification based on the analysisof the vectored group. Processing logic may migrate at least one of thedigital communication lines operating external to the vectored group tooperating within the vectored group. For example, reallocate, reassignor reconfigure a non-vectored line into a vectored group, or from onevectored group to another vectored group.

At block 625, processing logic performs noise-typing for an interferencesignal based on the analysis of the vectored group and identifying asource of the interference signal based on the noise-typing (e.g.,identify PSD and type of an alien crosstalker, correlating an aliencrosstalker with a line, and calculating an estimated performance gain).For example, processing logic may identify transmit Power SpectralDensity (PSD) and a type of an alien crosstalker based on a crosstalkcoupling frequency or a crosstalk coupling frequency range affecting oneor more of the plurality of digital communication lines in the vectoredgroup based on the analysis of the vectored group. Such processing logicmay correlate the alien crosstalker with one of the plurality of lineswhich operate external to the vectored group or with one of theplurality of digital communication lines in the vectored group based onthe crosstalk coupling frequency or the crosstalk coupling frequencyrange associated with the alien crosstalker. Processing logic maycalculate an estimated performance gain attributable to issuing theoptimization instructions and compare it to a threshold or use thecalculation to determine whether to initiate optimization instructionsand what optimization instructions to initiate.

FIG. 7 illustrates a diagrammatic representation of a machine 700 in theexemplary form of a computer system, in accordance with one embodiment,within which a set of instructions, for causing the machine 700 toperform any one or more of the methodologies discussed herein, may beexecuted. In alternative embodiments, the machine may be connected,networked, interfaced, etc., with other machines in a Local Area Network(LAN), a Wide Area Network, an intranet, an extranet, or the Internet.The machine may operate in the capacity of a server or a client machinein a client-server network environment, or as a peer machine in apeer-to-peer (or distributed) network environment. Certain embodimentsof the machine may be in the form of a personal computer (PC), a tabletPC, a set-top box (STB), a Personal Digital Assistant (PDA), a cellulartelephone, a web appliance, a server, a network router, switch orbridge, computing system, or any machine capable of executing a set ofinstructions (sequential or otherwise) that specify actions to be takenby that machine. Further, while only a single machine is illustrated,the term “machine” shall also be taken to include any collection ofmachines (e.g., computers) that individually or jointly execute a set(or multiple sets) of instructions to perform any one or more of themethodologies discussed herein.

The exemplary computer system 700 includes a processor 702, a mainmemory 704 (e.g., read-only memory (ROM), flash memory, dynamic randomaccess memory (DRAM) such as synchronous DRAM (SDRAM) or Rambus DRAM(RDRAM), etc., static memory such as flash memory, static random accessmemory (SRAM), volatile but high-data rate RAM, etc.), and a secondarymemory 718 (e.g., a persistent storage device including hard disk drivesand persistent data base implementations), which communicate with eachother via a bus 730. Main memory 704 includes information andinstructions and software program components necessary for performingand executing the functions with respect to the various embodiments ofthe systems, methods, and DSM server as described herein. Optimizationinstructions 723 may be triggered based on, for example, analysis ofneighborhood information, SNR data, PSD data, noise levels withmitigation active and noise levels with mitigation inactive, and soforth. Collected data and calculations 724 are stored within main memory704. Optimization instructions 723 may be stored within main memory 704and as collected and determined by DSM server 734. Main memory 704 andits sub-elements (e.g. 723 and 724) are operable in conjunction withprocessing logic 726 and/or software 722 and processor 702 to performthe methodologies discussed herein.

Processor 702 represents one or more general-purpose processing devicessuch as a microprocessor, central processing unit, or the like. Moreparticularly, the processor 702 may be a complex instruction setcomputing (CISC) microprocessor, reduced instruction set computing(RISC) microprocessor, very long instruction word (VLIW) microprocessor,processor implementing other instruction sets, or processorsimplementing a combination of instruction sets. Processor 702 may alsobe one or more special-purpose processing devices such as an applicationspecific integrated circuit (ASIC), a field programmable gate array(FPGA), a digital signal processor (DSP), network processor, or thelike. Processor 702 is configured to execute the processing logic 726for performing the operations and functionality which is discussedherein.

The computer system 700 may further include one or more networkinterface cards 708 to communicatively interface the computer system 700with one or more networks 720 from which information may be collectedfor analysis. The computer system 700 also may include a user interface710 (such as a video display unit, a liquid crystal display (LCD), or acathode ray tube (CRT)), an alphanumeric input device 712 (e.g., akeyboard), a cursor control device 714 (e.g., a mouse), and a signalgeneration device 716 (e.g., an integrated speaker). The computer system700 may further include peripheral device 736 (e.g., wireless or wiredcommunication devices, memory devices, storage devices, audio processingdevices, video processing devices, etc.). The computer system 700 mayperform the functions of a DSM server 734 capable interfacing withdigital communication lines in vectored and non-vectored groups,monitoring, collecting, analyzing, and reporting information, andinitiating, triggering, and executing various optimization instructions723 including the execution of commands and instructions to altercharacteristics and operation of vectoring mechanisms.

The secondary memory 718 may include a non-transitory machine-readablestorage medium (or more specifically a non-transitory machine-accessiblestorage medium) 731 on which is stored one or more sets of instructions(e.g., software 722) embodying any one or more of the methodologies orfunctions described herein. Software 722 may also reside, oralternatively reside within main memory 704, and may further residecompletely or at least partially within the processor 702 duringexecution thereof by the computer system 700, the main memory 704 andthe processor 702 also constituting machine-readable storage media. Thesoftware 722 may further be transmitted or received over a network 720via the network interface card 708.

While the subject matter disclosed herein has been described by way ofexample and in terms of the specific embodiments, it is to be understoodthat the claimed embodiments are not limited to the explicitlyenumerated embodiments disclosed. To the contrary, the disclosure isintended to cover various modifications and similar arrangements aswould be apparent to those skilled in the art. Therefore, the scope ofthe appended claims should be accorded the broadest interpretation so asto encompass all such modifications and similar arrangements. It is tobe understood that the above description is intended to be illustrative,and not restrictive. Many other embodiments will be apparent to those ofskill in the art upon reading and understanding the above description.The scope of the disclosed subject matter is therefore to be determinedin reference to the appended claims, along with the full scope ofequivalents to which such claims are entitled.

What is claimed is:
 1. A system comprising: an interface to a firstsubset of a plurality of digital communication lines allocated to avectored group and to a second subset of the plurality of digitalcommunication lines which operate external to the vectored group; aDynamic Spectral Management server (DSM server) to analyze the vectoredgroup by performing the following operations for each of the pluralityof digital communication lines in the vectored group: measure amitigated noise level for the digital communication line with crosstalkcancellation active, measure a non-mitigated noise level for the digitalcommunication line with crosstalk cancellation inactive, and compare themitigated noise level measured on the digital communication line withthe non-mitigated noise level measured on the digital communicationline; and wherein the DSM server is further to issue optimizationinstructions based on the analysis.
 2. The system of claim 1, whereinthe DSM server to issue the optimization instructions based on theanalysis comprises one of: (a) the DSM server to issue the optimizationinstructions for the vectored group; (b) the DSM server to issue theoptimization instructions for one or more of the digital communicationlines which operate external to the vectored group; and (c) the DSMserver to issue the optimization instructions for both the vectoredgroup and for one or more of the digital communication lines whichoperate external to the vectored group.
 3. The system of claim 1:wherein the plurality of digital communication lines comprises aplurality of Digital Subscriber Lines (DSL lines); and wherein the firstsubset of the plurality of digital communication lines allocated to thevectored group comprises a plurality of vectored DSL lines.
 4. Thesystem of claim 1, wherein the DSM server to analyze the vectored groupfurther comprises the DSM server to calculate an estimated noise leveland an estimated crosstalk level for each of the plurality of digitalcommunication lines in the vectored group.
 5. The system of claim 4,wherein the DSM server to calculate the estimated noise level and theestimated crosstalk level based at least in part on a measured signal tonoise ratio, SNR(f), for each of the plurality of digital communicationlines in the vectored group.
 6. The system of claim 4, wherein the DSMserver to calculate the estimated noise level for each of the pluralityof digital communication lines in the vectored group comprises the DSMserver to calculate the total Far End Crosstalk (FEXT) Power SpectralDensity (PSD) received by each of the plurality of digital communicationlines in the vectored group.
 7. The system of claim 4: wherein themitigated noise level represents a first amount of noise measured on therespective digital communication line within the vectored group whilenoise cancellation techniques are active to cancel out crosstalkattributable to other digital communication lines within the samevectored group; wherein the non-mitigated noise level represents asecond amount of noise measured on the respective digital communicationline within the vectored group while noise cancellation techniques areinactive, wherein the second amount of noise measured includesuncancelled interference from the other digital communication lineswithin the same vectored group; and wherein a baseline level ofinterference is estimated by subtracting a total crosstalk level XT(f)based on Xlog from the non-mitigated noise level.
 8. The system of claim7: wherein the DSM server to further measure a Signal-to-Noise Ratio,SNR(f), for each of the plurality of digital communication lines in thevectored group; wherein the SNR(f) and Quiet Line Noise Power SpectralDensity, QLN(f), for each of the plurality of digital communicationlines in the vectored group are used by the DSM server to calculate: themitigated noise level; the non-mitigated noise level; and the baselinelevel of interference on the respective digital communication linewithin the vectored group when the interference attributable to theother digital communication lines within the same vectored group isperfectly canceled.
 9. The system of claim 7, wherein the estimatedbaseline level of interference comprises at least one of: an estimatedlevel of interference attributable to receiver electronics, the receiverelectronics being part of a receiver coupled with one of the pluralityof digital communication lines; and an estimated level of interferenceattributable to an imperfect implementation of the crosstalkcancellation for the vectored group; an estimated level of crosstalkinterference which was cancelled by vectoring within the vectored group.10. The system of claim 4, wherein the DSM server is further to:identify transmit Power Spectral Density (PSD) and a type of an aliencrosstalker based on a crosstalk coupling frequency or a crosstalkcoupling frequency range affecting one or more of the plurality ofdigital communication lines in the vectored group based on the analysisof the vectored group.
 11. The system of claim 10: wherein the DSMserver is further to correlate the alien crosstalker with one of theplurality of lines in the second subset of digital communication lineswhich operate external to the vectored group or with one of theplurality of digital communication lines in the vectored group based onthe crosstalk coupling frequency or the crosstalk coupling frequencyrange associated with the alien crosstalker; and wherein the DSM serveris further to calculate an estimated performance gain attributable toissuing the optimization instructions, wherein the optimizationinstructions include noise cancellation directed toward the identifiedalien crosstalker.
 12. The system of claim 10, wherein the DSM server isfurther to identify an alien crosstalker based on the analysis of thevectored group, wherein the alien crosstalker corresponds to one of: anon-vectored digital communication line among the plurality of digitalcommunication lines; a non-vectored digital communication line within acommon binder with the plurality of digital communication lines in thevectored group; and a non-vector-friendly digital communication lineamong the plurality of digital communication lines within the vectoredgroup, wherein the non-vector-friendly digital communication line iscommunicably interfaced with a non-vector-friendly Digital SubscriberLine Modem (DSL modem) which does not support vectoring or does notimplement vectoring.
 13. The system of claim 10: wherein the DSM serveris further to correlate the alien crosstalker with one of the pluralityof lines in the second subset of digital communication lines whichoperate external to the vectored group or with one of the plurality ofdigital communication lines in the vectored group based on neighborhoodinformation using DSM level 2 joint spectral optimization among aselection of vectored lines, vector-friendly lines, and/ornon-vector-friendly lines within the first and second subsets of digitalcommunication lines which operate within and external to the vectoredgroup respectively.
 14. The system of claim 1, wherein the DSM server isfurther to: perform noise-typing of an interference signal based on theanalysis of the vectored group; and identify a source of theinterference signal based on the noise-typing.
 15. The system of claim1, wherein the DSM server to analyze the vectored group furthercomprises the DSM server to: estimate theoretical Far end crosstalk(FEXT); compare the estimated theoretical FEXT to the mitigated noiselevels measured for the plurality of digital communication lines in thevectored group; determine effectiveness of the crosstalk cancellationfor the vectored group; and issue commands to a Vectoring Control Entity(VCE) communicably interfaced with the vectored group.
 16. The system ofclaim 1: wherein the DSM server is further to calculate an estimatedperformance gain based on the analysis of the vectored group; andcompare the estimated performance gain against a threshold.
 17. Thesystem of claim 16, wherein a first alien crosstalker inside of thevectored group yields an estimated performance gain which is less thanan estimated performance gain for a second alien crosstalker external tothe vectored group, wherein the first alien crosstalker corresponds toone of the first subset of digital communication lines allocated to thevectored group and wherein the second alien crosstalker corresponds toone of the second subset of digital communication lines to operateexternal to the vectored group.
 18. The system of claim 1: wherein theDSM server is to further identify an alien crosstalker among theplurality of digital communication lines based on the analysis of thevectored group; and wherein the DSM server is to issue the optimizationinstructions for the vectored group based on the alien crosstalker beingidentified as one of the plurality of digital communication linesexternal to the vectored group.
 19. The system of claim 1, wherein theDSM server is further to: identify one or more digital communicationlines external to the vectored group based on the analysis of thevectored group; and perform at least one of the following operations forthe identified one or more digital communication lines external to thevectored group: a) change system parameters affecting the at least oneof the digital communication lines external to the vectored group, andb) migrate the at least one of the digital communication lines whichoperates external to the vectored group to operate within the vectoredgroup.
 20. A method comprising: communicably interfacing with aplurality of digital communication lines; identifying, within theplurality of digital communication lines, a vectored group having aplurality of digital communication lines allocated thereto; analyzingthe vectored group by performing the following operations for each ofthe plurality of digital communication lines in the vectored group:measuring a mitigated noise level for the digital communication linewith crosstalk cancellation active, measuring a non-mitigated noiselevel for the digital communication line with crosstalk cancellationinactive, and comparing the mitigated noise level measured on thedigital communication line with the non-mitigated noise level measuredon the digital communication line; and issuing optimization instructionsfor the vectored group based on the analysis.
 21. The method of claim20, wherein analyzing the vectored group comprises a Dynamic SpectrumManagement server (DSM server) analyzing the vectored group byperforming the operations.
 22. The method of claim 21, wherein the DSMserver is operated and managed by an entity which is separate anddistinct from a telecommunications operator responsible for theplurality of digital communication lines.
 23. The method of claim 20,wherein issuing the optimization instructions for the vectored groupcomprises: changing one or more parameters affecting operation of thevectored group, the one or more parameters being selected from the groupcomprising: bit rate, margin, Power Spectral Density (PSD) limits,vectoring resource allocations, Impulse Noise Protection (INP) settings.24. The method of claim 23: wherein the plurality of digitalcommunication lines comprise a plurality of Digital Subscriber Lines(DSL lines); and wherein changing the one or more parameters affectingoperation of the vectored group comprises issuing the optimizationinstructions to change the one or more parameters in at least one of: aDigital Subscriber Line Access Multiplexer (DSLAM) communicablyinterfaced with at least one of the plurality of digital communicationlines in the vectored group, one or more DSLAMs adjacent to the firstDSLAM, a Customer Premises Equipment (CPE) modem communicably interfacedwith at least one of the plurality of digital communication lines in thevectored group, and a DSL Element Management System (EMS) communicablyinterfaced with at least one of the plurality of digital communicationlines in the vectored group.
 25. The method of claim 20, wherein issuingthe optimization instructions for the vectored group comprises: a)dispatching orders to modify a configuration of one or more systemelements communicably interfaced with at least one of the plurality ofcommunicably interfaced digital communication lines; b) generatingservice recommendations including service upgrades, service downgrades,or different service options, based on the analysis of the vectoredgroup; c) initiating a customer notification based on the analysis ofthe vectored group, the customer notification being directed to acustomer of services associated with one of the plurality ofcommunicably interfaced digital communication lines; and d) initiating aservice provider notification based on the analysis of the vectoredgroup, the service provider notification being directed to a serviceprovider of services associated at least one of the plurality ofcommunicably interfaced digital communication lines.
 26. The method ofclaim 20, further comprising: identifying transmit Power SpectralDensity (PSD) and a type of an alien crosstalker based on a crosstalkcoupling frequency or a crosstalk coupling frequency range affecting oneor more of the plurality of digital communication lines in the vectoredgroup based on the analysis of the vectored group.
 27. The method ofclaim 26, further comprising: correlating the alien crosstalker with oneof the plurality of lines which operate external to the vectored groupor with one of the plurality of digital communication lines in thevectored group based on the crosstalk coupling frequency or thecrosstalk coupling frequency range associated with the aliencrosstalker; and calculating an estimated performance gain attributableto issuing the optimization instructions, wherein the optimizationinstructions include noise cancellation directed toward the identifiedalien crosstalker.
 28. The method of claim 20, further comprising:identifying an alien crosstalker based on the analysis of the vectoredgroup, wherein the alien crosstalker corresponds to one of: anon-vectored digital communication line among the plurality of digitalcommunication lines; a non-vectored digital communication line within acommon binder with the plurality of digital communication lines in thevectored group; and a non-vector-friendly digital communication lineamong the plurality of digital communication lines within the vectoredgroup, wherein the non-vector-friendly digital communication line iscommunicably interfaced with a non-vector-friendly Digital SubscriberLine Modem (DSL modem) which does not support vectoring or does notimplement vectoring.
 29. The method of claim 20, further comprising:noise-typing an interference signal based on the analysis of thevectored group; and identifying a source of the interference signalbased on the noise-typing.
 30. The method of claim 20, wherein analyzingthe vectored group further comprises: estimating theoretical Far endcrosstalk (FEXT); comparing the estimated theoretical FEXT to themitigated noise levels measured for the plurality of digitalcommunication lines in the vectored group; determining effectiveness ofthe crosstalk cancellation for the vectored group; and issuing commandsto a Vectoring Control Entity (VCE) communicably interfaced with thevectored group.
 31. The method of claim 20, further comprising:calculating an estimated performance gain based on the analysis of thevectored group; and comparing the estimated performance gain against athreshold.
 32. The method of claim 20, wherein issuing the optimizationinstructions for the vectored group comprises issuing the optimizationinstructions based an identified alien crosstalker operating as one ofthe plurality of digital communication lines external to the vectoredgroup and not as a member of the vectored group.
 33. The method of claim20, wherein issuing the optimization instructions for the vectored groupcomprises performing at least one of the following operations: a)changing system parameters affecting at least one of the digitalcommunication lines operating external to the vectored group, and b)migrating at least one of the digital communication lines operatingexternal to the vectored group to operating within the vectored group.34. A non-transitory computer readable storage medium havinginstructions stored thereon that, when executed by a processor in aDynamic Spectrum Management server (DSM server), the instructions causethe DSM server to perform operations comprising: communicablyinterfacing with a plurality of digital communication lines;identifying, within the plurality of digital communication lines, avectored group having a plurality of digital communication linesallocated thereto; analyzing the vectored group by performing thefollowing sub-operations for each of the plurality of digitalcommunication lines in the vectored group: measuring a mitigated noiselevel for the digital communication line with crosstalk cancellationmitigation active, measuring a non-mitigated noise level for the digitalcommunication line with crosstalk cancellation mitigation inactive, andcomparing the mitigated noise level measured on the digitalcommunication line with the non-mitigated noise level measured on thedigital communication line; and issuing optimization instructions forthe vectored group based on the analysis.
 35. The non-transitorycomputer readable storage medium of claim 34, wherein the instructionscause the DSM server to perform operations further comprising:estimating theoretical Far end crosstalk (FEXT); comparing the estimatedtheoretical FEXT to the mitigated noise levels measured for theplurality of digital communication lines in the vectored group;determining effectiveness of the crosstalk cancellation for the vectoredgroup; and issuing commands to a Vectoring Control Entity (VCE)communicably interfaced with the vectored group.